The disclosed embodiments relate to processing an electrocardiograph signal, such as a system for processing an electrocardiograph signal to identify instances of interest in the signal.
Electrocardiography (ECG) is a transthoracic (e.g., across the thorax or chest) interpretation of the electrical activity of the heart over a period of time, as detected by electrodes attached to the outer surface of the skin or at specific loci of the heart via cardiac catheters and recorded by an electrocardiograph external to the body. The electrical activities of the heart are recorded as signals by the electrocardiograph. The signals recorded from the surface of the skin are referred to as surface electrocardiograph signals and the signals from the internal part of the heart are referred to as intracardiac electrograph signals.
ECG with the electrodes at the outer surface of the skin is useful to measure the rate and regularity of heartbeats, the size and position of the chambers, the presence of any damage to the heart, and the effects of drugs or devices used to regulate the heart (such as a pacemaker). While the intracardiac electrograph signals help to detect cardiac arrhythmias, detection of some heart diseases, such as cardiac arrhythmias, involves a great degree of accuracy in identifying few instances of interest in each of the signals. Based on these instances individually and in combination, a physician decides on the occurrence or non-occurrence of the disease in a patient.
One possible way for identifying the instances of interest in signals is by automated segmentation of the signals using frequency and time domain template matching methods, such as correlation waveform analysis, which is independent of amplitude fluctuation and ICE baseline. Correlation waveform analysis is effective in discriminating ventricular depolarizations in sinus rhythm (SR) from indications of ventricular tachycardia (VT), and in differentiating morphologically distinct ventricular tachycardias in the same patient. Another way is based on a difference of area (DOA) scheme, which is dependent upon amplitude fluctuation and ICE baseline. These methods are based on simple criteria, such as the difference of areas between the template and the test signal. The methods have a limitation in connection with the variability in the test signals. The limitation may be met by increasing the number of templates. But incrementing the number of templates leads to increased computation time. Further, these methods implicitly rely on the P wave onset point, which, in some cases, cannot be computed accurately.